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At least 955 records · Page 53

A Priori Analysis of Flamelet-Based Modeling for a Dual-Mode Scramjet Combustor

An a priori investigation of the applicability of flamelet-based combustion models to dual-mode scramjet combustion was performed utilizing Reynolds-averaged simulations (RAS). For this purpose, the HIFiRE Direct Connect Rig (HDCR) flowpath, fueled with a JP-7 fuel surrogate and operating in dual- and scram-mode was considered. The chemistry of the JP-7 fuel surrogate was modeled using a 22 species, 18-step chemical reaction mechanism. Simulation results were compared to experimentally-obtained, time-averaged, wall pressure measurements to validate the RAS solutions. The analysis of the dual-mode operation of this flowpath showed regions of predominately non-premixed, high-Damkohler number, combustion. Regions of premixed combustion were also present but associated with only a small fraction of the total heat-release in the flow. This is in contrast to the scram-mode operation, where a comparable amount of heat is released from non-premixed and premixed combustion modes. Representative flamelet boundary conditions were estimated by analyzing probability density functions for temperature and pressure for pure fuel and oxidizer conditions. The results of the present study reveal the potential for a flamelet model to accurately model the combustion processes in the HDCR and likely other high-speed flowpaths of engineering interest.

Quinlan, Jesse R.↗

Seasonal Variations of Mercury's Magnesium Dayside Exosphere from MESSENGER Observations

The Ultraviolet and Visible Spectrometer channel of the Mercury Atmospheric and Surface Composition Spectrometer instrument aboard the MErcury Surface, Space ENvironment, GEochemistry, and Ranging spacecraft made near-daily observations of solar-scattered resonant emission from magnesium in Mercury's exosphere during the mission's orbital phase (March 2011-April 2015, approx.17 Mercury years). In this paper, a subset of these data (March 2013-April 2015) is described and analyzed to illustrate Mg's spatial and temporal variations. Dayside altitude profiles of emission are used to make estimates of the Mg density and temperature. The main characteristics of the Mg exosphere are (a) a predominant enhancement of emission in the morning (6 am-10 am) near perihelion, (b) a bulk temperature of approx. 6000 K, consistent with impact vaporization as the predominant ejection process, (c) a near-surface density that varies from 5/cu cm to 50/cu cm and (d) a production rate that is strongest in the morning on the inbound leg of Mercury's orbit with rates ranging from 1×10(exp 5)/sq cm/s to 8×10(exp 5)/sq cm/s.

Ultraviolet↗

On the Detectability of CO Molecules in the Interstellar Medium via X-Ray Spectroscopy

We present a study of the detectability of CO molecules in the Galactic interstellar medium using high-resolution X-ray spectra obtained with the XMM-Newton Reflection Grating Spectrometer. We analysed 10 bright low mass X-ray binaries (LMXBs) to study the CO contribution in their line of sights. A total of 25 observations were fitted with the ISMabs X-ray absorption model which includes photoabsorption cross-sections for Oi, Oii, Oiii and CO. We performed a Monte Carlo (MC) simulation analysis of the goodness of fit in order to estimate the significance of the CO detection. We determine that the statistical analysis prevents a significant detection of CO molecular X-ray absorption features, except for the lines of sight towards XTE J1718-330 and 4U 1636-53. In the case of XTE J1817-330, this is the first report of the presence of CO along its line of sight. Our results reinforce the conclusion that molecules have a minor contribution to the absorption features in the O K-edge spectral region. We estimate a CO column density lower limit to perform a significant detection with XMM-Newton of N(CO) greater than 6 x 10(exp 16) per sq cm for typical exposure times.

ISM: structure↗

Composition-property correlations in NiTi-based shape memory alloys from the first principles

Development of shape memory alloys (SMA) has been traditionally accomplished by means of extensive empirical efforts, with a very limited support from phenomenological models and related tools. We present a theoretical framework based on the Hamiltonian formalism, which connects important thermodynamic properties directly to the relative energies (the eigenvalues of the Hamiltonian), computed from the first principles using density functional theory. The estimates based on this formalism allow to establish correlations between composition and physical properties, such as relative energies, phase transition temperatures, hysteresis, thermal expansion, and other thermodynamic information. Importantly, estimates and correlations not only provide a fast answer, but also elucidate underpinning of thermodynamic features in terms of the electronic structure. Using this framework, we consider phase transformations and correlations between the selected properties and composition in the NiTi-based ternary and multicomponent shape memory alloys. Our theoretical guidance facilitates design and development of future alloys.

shape memory alloys↗

GW190814: Gravitational Waves from the Coalescence of a 23 Solar Mass Black Hole with a 2.6 Solar Mass Compact Object

We report the observation of a compact binary coalescence involving a 22.2–24.3 Me black hole and a compact object with a mass of 2.50–2.67Me (all measurements quoted at the 90% credible level). The gravitational-wavesignal, GW190814, was observed during LIGO’s and Virgo’s third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network. The source was localized to18.5 deg2 at a distance of-+2414541Mpc; no electromagnetic counterpart has been confirmed to date. The source has the most unequal mass ratio yet measured with gravitational waves,-+0.1120.0090.008, and its secondary component is either the lightest black hole or the heaviest neutron star ever discovered in a double compact-object system. The dimensionless spin of the primary black hole is tightly constrained to 0.07. Tests of general relativity reveal no measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at high confidence. We estimate a merger rate density of 1–23 Gpc−3yr−1 for the new class of binary coalescence sources that GW190814 represents. Astrophysical models predict that binaries with mass ratios similar to this event can form through several channels, but are unlikely to have formed in globular clusters. However, the combination of mass ratio, component masses, and the inferred merger rate for this event challenges all current models of the formation and mass distribution of compact-object binaries.

Gravitational wave astronomy↗

ALMA Observations of Molecular Complexity in the Large Magellanic Cloud: The N105 Star-Forming Region

The Large Magellanic Cloud (LMC) is the nearest laboratory for detailed studies on the formation and survival of complex organic molecules (COMs), including biologically important ones, in lowmetallicity environments—typical for earlier cosmological epochs. We report the results of 1.2 mm continuum and molecular line observations of three fields in the star-forming region N105 with the Atacama Large Millimeter/submillimeter Array (ALMA). N105 lies at the western edge of the LMC bar with on-going star formation traced by H2O, OH, and CH3OH masers, ultracompact Hii regions, and young stellar objects. Based on the spectral line modeling, we estimated rotational temperatures, column densities, and fractional molecular abundances for twelve 1.2 mm continuum sources. We identified sources with a range of chemical make-ups, including two bona fide hot cores and four hot core candidates. The CH3OH emission is widespread and associated with all the continuum sources. COMs CH3CN and CH3OCH3 are detected toward two hot cores in N105 together with smaller molecules typically found in Galactic hot cores (e.g., SO2, SO, and HNCO) with the molecular abundances roughly scaling with metallicity. We report a tentative detection of the astrobiologically relevant formamide molecule (NH2CHO) toward one of the hot cores; if confirmed, this would be the first detection of NH2CHO in an extragalactic sub-solar metallicity environment. We suggest that metallicity inhomogeneities resulting from the tidal interactions between the LMC and the Small Magellanic Cloud (SMC) might have led to the observed large variations in COM abundances in LMC hot cores.

Marta Sewilo↗

The Radio Fundamental Catalogue. I. Astrometry

We present the all-sky catalogue of absolute positions and estimates of correlated flux density of 21,942 compact radio sources determined from processing interferometric visibility data of virtually all VLBI observing sessions at 2 to 23~GHz from 72 programs suitable for absolute astrometry collected for 30 years. We used a novel technique of generation of a dataset of fused observables that allowed us to incorporate all available data in our analysis. The catalogue is the most complete and most precise to date. It forms the foundation and reference for positional astronomy, space geodesy, space navigation, population analysis of active galactic nuclei (AGNs), and provides calibrators for phase-referencing for differential astrometry and VLBI astrophysical observations. Its accuracy was evaluated through a detailed accounting systematic errors, rigorous decimation tests, comparison of different datasets, and comparison with other catalogues. The catalogue samples preferentially the AGNs with a strong contemporary parsec-scale synchrotron emission. Its milliarcsecond level positional accuracy allows association of these AGNs with detections in a wide range of the electromagnetic spectrum from low-frequency radio to gamma-rays and high energy neutrinos. We describe the innovative data processing and calibration technique in full detail, report the in depth analysis of random and systematic positional errors, and provide the list of associations with large surveys at different wavelengths.

Astronomy↗

Unbinned extraction of $γ$ from $B\to DK$ with normalizing flows

We introduce an unbinned method for extracting the CKM angle $γ$ from the decay chain $B^\pm \to (D \to K_S π^+ π^-) K^\pm$ using normalizing flows (NFs). The NFs, trained on $D$ decay data, learn a faithful continuous representation of the amplitude and strong phase variation over the $D\to K_Sπ^+π^-$ Dalitz plot whose fidelity improves with increased data sample sizes. With this input, the $B$ decay data can be used to extract the parameters $r_B$, $δ_B$, and $γ$. We test the method on Monte Carlo generated data, where it successfully recovers the injected value of $γ$ within uncertainties. The present implementation propagates statistical uncertainties from finite training data via an ensemble of independently trained flows, and does not attempt to capture the effects of systematic experimental errors. We explore two versions of the method that differ in how the trigonometric constraint on phase variation is encoded, and comment on the possible extension to Bayesian NFs, which would provide direct uncertainty estimates on the learned densities without requiring ensemble training.

Grossman, Yuval [Cornell U., LEPP]↗

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗

Improved canopy reflectance modeling and scene inference through improved understanding of scene pattern

The Li-Strahler reflectance model, driven by LANDSAT Thematic Mapper (TM) data, provided regional estimates of tree size and density within 20 percent of sampled values in two bioclimatic zones in West Africa. This model exploits tree geometry in an inversion technique to predict average tree size and density from reflectance data using a few simple parameters measured in the field (spatial pattern, shape, and size distribution of trees) and in the imagery (spectral signatures of scene components). Trees are treated as simply shaped objects, and multispectral reflectance of a pixel is assumed to be related only to the proportions of tree crown, shadow, and understory in the pixel. These, in turn, are a direct function of the number and size of trees, the solar illumination angle, and the spectral signatures of crown, shadow and understory. Given the variance in reflectance from pixel to pixel within a homogeneous area of woodland, caused by the variation in the number and size of trees, the model can be inverted to give estimates of average tree size and density. Because the inversion is sensitive to correct determination of component signatures, predictions are not accurate for small areas.

Franklin, Janet↗

Determining the general circulation of the ocean - A nonlinear inverse problem

The usual inversion procedures for determining the oceanic circulation take the density field as given. This does not explicitly account for the mismatch between the data (which are typically a single realization of the density field) and the circulation being estimated (which may be a time mean or some other smoothed quantity), but explicit consideration of the uncertainty of the density data renders the problem nonlinear, and new estimation methods have to be used. As an example, a nonlinear inversion is successfully applied here to the simple analytical model of Stommel and Veronis (1981). It is also shown that their linear procedure, if properly used, yields a much better result than they obtained.

Mercier, H.↗

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Soil Moisture Active Passive↗

Using Machine Learning to Estimate Surface-Level SO2 Concentrations from Satellite-Based Measurements

Sulfur dioxide (SO2) is a criteria air pollutant due to its contributions to aerosol formation, rainfall acidification, and harm to human health. The placement of air quality monitoring sites is typically biased towards urban areas, leaving large areas with very limited monitoring data. The Ozone Monitoring Instrument (OMI) has been used to provide estimates of SO2 vertical column densities (VCDs) globally at spatial resolution of 10s of kms once per day. OMI SO2 VCDs have been previously used to estimate surface SO2 concentrations using chemical transport model (CTM) simulations. The CTMs use estimated emissions and assimilated meteorological data, and simulate the chemical and physical processes that determine the vertical profile of SO2, which can be used to derive a ratio between the surface concentrations and VCDs. These models are complex, computationally expensive, and have large uncertainties in the simulated surface-to-VCD ratio due to biases in emissions and relatively coarse resolution. Machine learning techniques are comparatively easier to use, much less computationally expensive to use after training, and can produce more accurate estimations of surface concentrations than the CTM-based method. The interpretation of machine learning models often poses challenges, and in some cases, non-physical variables unrelated to SO2 are used as predictors. In this work, we create an artificial neural network (ANN) to relate OMI retrievals and archived GEOS-FP boundary layer heights to surface SO2 concentrations from the ChinaHighAirPollutants ChinaHighSO2 dataset (CHAP; Wei et al., 2023) on a seasonal average timescale from 2013-2018. Our model only utilizes five variables that are directly relevant to the satellite retrieval, lifetime, and spatial distribution of SO2. The model was trained on 16 seasons (four of each) with independent validation (one of each season) and testing datasets (one of each season) to avoid overfitting. Our ANN generates surface SO2 concentrations that are sensitive (slope = 0.51) and consistent (r = 0.74) with the CHAP data, but are underpredicted by an average of 1.2 ppbv with a mean absolute error of 2.2 ppbv. These results are better than recent studies utilizing the CTM method. To our knowledge, this is the best performing machine learning model that only uses physical variables to predict surface SO2. Our work demonstrates that a carefully constructed, simple ML model can accurately estimate surface-based SO2 concentrations from satellite VCD measurements, and this technique has future promise to expend to newer, higher resolution satellites and other air pollutants.

SO2, air quality, OMI, machine learning↗

Experimental 3-dimensional tracking of the dynamics of a single electron in the Fermilab Integrable Optics Test Accelerator (IOTA)

We present the results of experimental studies on the transverse and longitudinal dynamics of a single electron in the IOTA storage ring. IOTA is a flexible machine dedicated to beam physics experiments with electrons and protons. A method was developed to reliably inject and circulate a controlled number of electrons in the ring. A key beam diagnostic system is the set of sensitive high-resolution digital cameras for the detection of synchrotron light emitted by the electrons. With 60–130 electrons in the machine, we measured beam lifetime and derived an absolute calibration of the optical system. At exposure times of 0.5 s, the cameras were sensitive to individual electrons. Camera images were used to reconstruct the time evolution of oscillation amplitudes of a single electron in all 3 degrees of freedom. The evolution of amplitudes directly showed the interplay between synchrotron-radiation damping, quantum excitations, and scattering with the residual gas. From the distribution of measured single-electron oscillation amplitudes, we deduced transverse emittances, momentum spread, damping times, and beam energy. Estimates of residual-gas density and composition were calculated from the measured distributions of vertical scattering angles. Combining scattering and lifetime data, we also provide an estimate of the aperture of the ring. To our knowledge, this is the first time that the dynamics of a single electron are tracked in all three dimensions with digital cameras in a storage ring.

43 PARTICLE ACCELERATORS↗

Mars-GRAM Applications for Mars Science Laboratory Mission Site Selection Processes

An overview is presented of the Mars-Global Reference Atmospheric Model (Mars-GRAM 2005) and its new features. One important new feature is the "auxiliary profile" option, whereby a simple input file is used to replace mean atmospheric values from Mars-GRAM's conventional (General Circulation Model) climatology. An auxiliary profile can be generated from any source of data or alternate model output. Results are presented using auxiliary profiles produced from mesoscale model output (Southwest Research Institute's Mars Regional Atmospheric Modeling System (MRAMS) model and Oregon State University's Mars mesoscale model (MMM5) model) for three candidate Mars Science Laboratory (MSL) landing sites (Terby Crater, Melas Chasma, and Gale Crater). A global Thermal Emission Spectrometer (TES) database has also been generated for purposes of making 'Mars-GRAM auxiliary profiles. This data base contains averages and standard deviations of temperature, density, and thermal wind components, averaged over 5-by-5 degree latitude bins and 15 degree L(sub S) bins, for each of three Mars years of TES nadir data. Comparisons show reasonably good consistency between Mars-GRAM with low dust optical depth and both TES observed and mesoscale model simulated density at the three study sites. Mean winds differ by a more significant degree. Comparisons of mesoscale and TES standard deviations' with conventional Mars-GRAM values, show that Mars-GRAM density perturbations are somewhat conservative (larger than observed variability), while mesoscale-modeled wind variations are larger than Mars-GRAM model estimates. Input parameters rpscale (for density perturbations) and rwscale (for wind perturbations) can be used to "recalibrate" Mars-GRAM perturbation magnitudes to better replicate observed or mesoscale model variability.

Justh, Hilary↗

Assessment of DFT functionals for a minimal nitrogenase [Fe(SH) 4 H]- model employing state-of-the-art ab initio methods

We have designed a [Fe(SH)4H]- model with the fifth proton binding either to Fe or S. We show that the energy difference between these two isomers (ΔE) is hard to estimate with quantum-mechanical (QM) methods. For example, different density functional theory (DFT) methods give ΔE estimates that vary by almost 140 kJ/mol, mainly depending on the amount of exact Hartree–Fock included (0%–54%). The model is so small that it can be treated by many high-level QM methods, including coupled-cluster (CC) and multiconfigurational perturbation theory approaches. With extrapolated CC series (up to fully connected coupled-cluster calculations with singles, doubles, and triples) and semistochastic heat-bath configuration interaction methods, we obtain results that seem to be converged to full configuration interaction results within 5 kJ/mol. Our best result for ΔE is 101 kJ/mol. With this reference, we show that M06 and B3LYP-D3 give the best results among 35 DFT methods tested for this system. Brueckner doubles coupled cluster with perturbaitve triples seems to be the most accurate coupled-cluster approach with approximate triples. CCSD(T) with Kohn–Sham orbitals gives results within 4–11 kJ/mol of the extrapolated CC results, depending on the DFT method. Single-reference CC calculations seem to be reasonably accurate (giving an error of ~5 kJ/mol compared to multireference methods), even if the D1 diagnostic is quite high (0.25) for one of the two isomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SOFIA 2 model telescope wind tunnel test report

This document outlines the tests performed to make aerodynamic force and torque measurements on the SOFIA wind tunnel model telescope. These tests were performed during the SOFIA 2 wind tunnel test in the 14 ft wind tunnel during the months of June through August 1994. The test was designed to measure the dynamic cross elevation moment acting on the SOFIA model telescope due to aerodynamic loading. The measurements were taken with the telescope mounted in an open cavity in the tail section of the SOFIA model 747. The purpose of the test was to obtain an estimate of the full scale aerodynamic disturbance spectrum, by scaling up the wind tunnel results (taking into account differences in sail area, air density, cavity dimension, etc.). An estimate of the full scale cross elevation moment spectrum was needed to help determine the impact this disturbance would have on the telescope positioning system requirements. A model of the telescope structure, made of a light weight composite material, was mounted in the open cavity of the SOFIA wind tunnel model. This model was mounted via a force balance to the cavity bulkhead. Despite efforts to use a 'stiff' balance, and a lightweight model, the balance/telescope system had a very low resonant frequency (37 Hz) compared to the desired measurement bandwidth (1000 Hz). Due to this mechanical resonance of the balance/telescope system, the balance alone could not provide an accurate measure of applied aerodynamic force at the high frequencies desired. A method of measurement was developed that incorporated accelerometers in addition to the balance signal, to calculate the aerodynamic force.

Keas, Paul↗